Department of Chemistry, Faculty of Science, Ain Shams University, Abbassia, Cairo 11566, Egypt.
Food Chem. 2019 Feb 15;274:360-367. doi: 10.1016/j.foodchem.2018.09.014. Epub 2018 Sep 5.
Portable, sensitive and cost-effective sensors represent an unmet need, especially in resource-limited settings and locally deprived communities. Digital imaging devices can fill the gap. Thus, we have tested a desktop scanner, a digital camera and a smartphone to determine iron using three standard colour reactions. Images of reacting solutions were analysed to obtain the RGB (red, green and blue) non-uniform colour space parameters. To improve the calibration linearity, sensitivity, and detection limit, we converted the RGB intensities into six uniform colour space values and two colour differences attributes. The converted signals surpassed the RGB signals and compared well with reference spectrophotometric signals. The simplicity and sensitivity of this approach make digital imaging devices as excellent competitors to field-monitoring instruments and sophisticated spectrophotometers. Our approach was successfully applied to the assessment of iron in Nile river water, soils, plant materials and meat and liver samples.
便携式、灵敏且经济实惠的传感器是目前尚未满足的需求,特别是在资源有限的环境和当地贫困社区中。数字成像设备可以填补这一空白。因此,我们已经测试了桌面扫描仪、数码相机和智能手机,以使用三种标准显色反应来检测铁。对反应溶液的图像进行分析以获得 RGB(红、绿、蓝)非均匀颜色空间参数。为了提高校准线性度、灵敏度和检测限,我们将 RGB 强度转换为六个均匀颜色空间值和两个颜色差属性。转换后的信号优于 RGB 信号,并且与参考分光光度信号相比表现良好。这种方法的简单性和灵敏度使数字成像设备成为现场监测仪器和复杂分光光度计的绝佳竞争对手。我们的方法成功应用于评估尼罗河水、土壤、植物材料以及肉类和肝脏样本中的铁含量。